z-logo
open-access-imgOpen Access
Big Data analysis in development of personalized medical system
Author(s) -
Nataliya Shakhovska,
Соломія Федушко,
Michal Greguš,
Nataliia Melnykova,
Iryna Shvorob,
Yuriy Syerov
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.09.461
Subject(s) - computer science , personalization , ontology , big data , scheme (mathematics) , process (computing) , semantics (computer science) , medical information , information retrieval , data mining , data science , world wide web , mathematical analysis , philosophy , mathematics , epistemology , programming language , operating system
This paper considers the actual problem of Big Data analysis of medical information. Big Data is characterized by heterogeneity and constant growth requires the use of non-standard approaches to storage and processing of data. The analysis of personalized medical information for system development is proposed. The methods of construction of patient information track model based on systematic verification of patient’s personal and medical data is developed. The semantics of the data personalization in decision-making consists of the following stags: stage of forming the ontology of medical knowledge of the medical process and stage of formalizing the process of finding standard solutions. A personalized approach to personalization of standard schemes is proposed by modifying the decision-making method based on decision trees, taking into account the relationship between patient parameters. The result of the method is presented in personalized scheme.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom